This visualization product displays the total abundance of marine macro-litter (> 2.5cm) per beach per year from non-MSFD monitoring surveys, research & cleaning operations. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols and reference lists used on a European scale. Preliminary processing were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of surveys from non-MSFD monitoring, cleaning and research operations; - Exclusion of beaches without coordinates; - Some categories & some litter types like organic litter, small fragments (paraffin and wax; items > 2.5cm) and pollutants have been removed. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines and EU Threshold Value for Macro Litter on Coastlines from JRC (these two documents are attached to this metadata). - Exclusion of surveys without associated length; - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of items (normalized by 100 m) = Number of litter per items x (100 / survey length) Then, this normalized number of items is summed to obtain the total normalized number of litter for each survey. Finally, the median abundance for each beach and year is calculated from these normalized abundances per survey. Percentiles 50, 75, 95 & 99 have been calculated taking into account other sources data for all years. More information is available in the attached documents. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area.

'''Short description:''' Multi-Year mono-mission satellite-based along-track significant wave height. Only valid data are included, based on a rigorous editing combining various criteria such as quality flags (surface flag, presence of ice) and thresholds on parameter values. Such thresholds are applied on parameters linked to significant wave height determination from retracking (e.g. SWH, sigma0, range, off nadir angle…). All the missions are homogenized with respect to a reference mission and in-situ buoy measurements. Finally, an along-track filter is applied to reduce the measurement noise. This product is based on the ESA Sea State Climate Change Initiative data Level 3 product (version 2) and is formatted by the WAVE-TAC to be homogeneous with the CMEMS Level 3 Near-real-time product. It is based on the reprocessing of GDR data from the following altimeter missions: Jason-1, Jason-2, Envisat, Cryosat-2, SARAL/AltiKa and Jason-3. CFOSAT Multi-Year dataset is based on the reprocessing of CFOSAT Level-2P products (CNES/CLS), inter-calibrated on Jason-3 reference mission issued from the CCI Sea State dataset. One file containing valid SWH is produced for each mission and for a 3-hour time window. It contains the filtered SWH (VAVH) and the unfiltered SWH (VAVH_UNFILTERED). '''DOI (product) :''' https://doi.org/10.48670/moi-00176

This dataset contains OAC-P results from application to Argo data in the World Ocean : - the 2000-2015 climatology of OAC-P results mapped onto a 0.5x0.5 grid with mapping error estimates; - the 2000-2015 probability density function of the permanent pycnocline potential density referenced to the sea surface vs Brunt-Väisälä frequency squared.OAC-P is an "Objective Algorithm for the Characterization of the permanent Pycnocline" developed to characterize subtropical gyre stratification features with both observed and modeled potential density profiles. OAC-P estimates the following properties: - for the permanent pycnocline: depth, upper and lower thicknesses, Brunt-Väisälä frequency squared, potential density, temperature and salinity; - for the surface mode water overlying the permanent pycnocline: depth, Brunt-Väisälä frequency squared, potential density, temperature and salinity. Argo data were download from Coriolis Argo GDAC on February, 8th 2016. Only Argo data with QC=1, 2, 5 or 8 were used.

The data come from organisms and pictures collected during the MEDITS annual bottom trawl surveys conducted between 2011 and 2013 (Bertrand et al. 2002). MEDITS surveys cover the continental shelf (10 m to 200 m depth) and the upper part of the continental slope (200 m to 800 m) on the Mediterranean. A total of 1511 individuals from 85 fish species were collected from seven Mediterranean areas (South Adriatic Sea, Sardinia, Gulf of Lions, around Cyprus, Mallorca, Tyrrhenian Sea, and North West Ionian Sea). A set of 14 morphological traits related to the habitat and the diet of the species were measured in the field and on pictures using the ImageJ software (version 1.47, http://imagej.nih.gov/ij/) (see Granger et al. 2015 and Brind'Amour et al. submitted for details) (Figure 1). Replicats of measures vary between 1 (e.g. Scorpaena loppei) to 53 (e.g. Serranus hepatus) according to fish species. Twelve of the chosen traits consist in continuous biological characteristics measured on each individual (measured in cm). The two remaining traits are categorical and determined at the species level.

This map presents all layers corresponding to "Inland freight water transport" activities in the Atlantic area. For more information about this NACE code : https://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=DSP_NOM_DTL_VIEW&StrNom=NACE_REV2&StrLanguageCode=EN&IntPcKey=18512804&IntKey=18513014&StrLayoutCode=HIERARCHIC&IntCurrentPage=1 Indicators collected are : Business indicators per country

Gironde estuary environmental parameters and SPM maps generated from 41 Landsat-8/OLI and Sentinel-2/MSI images acquired over the period 2013-2018. Except bathymetry and daily river discharge data, that are accessible on public platforms, the dataset includes all of the time seris used in the publication: Analysis of suspended sediment variability in a large highly-turbid estuary using a 5-year-long remotely-sensed data archive at high resolution, Journal of Geophysical Research: Oceans, DOI:10.1029/2019JC015417.

Questions: Invasiveness depends in part on the ability of exotic species to either exclude native dominants or to fill an empty niche. Comparisons of niches and effects of closely related native and invasive species enable the investigation of this topic. Does Spartina anglica invade European salt marshes through competitive exclusion of the native Spartina maritima or due to the occurrence of an empty ecological niche in highly anoxic conditions? Location: The Arcachon Bay (France). Methods: At three intertidal levels, we quantified competitive response and effect abilities of the two species through a cross-transplantation removal experiment. We also compared at three intertidal levels the biomass, root/shoot ratio, productivity and environmental conditions (elevation, salinity, potential redox and soil moisture) of salt marsh communities dominated by the exotic Spartina anglica or the native Spartina maritima. Results: Both established species showed similar biotic resistance to the invasion of the other species, but the exotic showed important intraspecific facilitation for growth. Species had similar niches and total biomass along a gradient of anoxic conditions, but the exotic had a much higher root/shoot ratio and productivity than the native. Owing to its rhizome density, the exotic showed a high ability to increase sediment oxygenation, likely to explain its important intraspecific facilitation. Conclusions: Our results showed that the invasion success of S. anglica cannot be explained by the competitive exclusion of the native or by its ability to fill an empty niche along a gradient of anoxia. Its behaviour as a self-facilitator invasive engineer is very likely to explain its rapid spread in the Bay and biotic resistance to the colonization of other congeneric species when established in dense patches. Additionally, we suggest that physical disturbance in the marsh communities dominated by the native S. maritima may disrupt its biotic resistance against the invasion of S. anglica.

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). This regional aggregated dataset contains all unrestricted EMODnet Chemistry data on contaminants; temperature, salinity and additional sampling parameters are included when available. The spatial coverage is the Mediterranean Sea with 10917 CDI records divided per matrices: 3095 water profiles and 1385 water timeseries, 1511 sediment profiles and 4083 sediment timeseries, 42 biota profiles and 801 biota timeseries. In the water datasets, the vertical profiles temporal range is from 1974-09-12 to 2015-12-11 and the timeseries temporal range is from 2006-08-17 to 2018-04-26. In the sediment datasets, vertical profiles temporal range is from 1971-01-12 to 2016-04-07 and time series temporal range is from 1981-06-27 to 2018-12-14. For the biota datasets, vertical profiles temporal range is from 2008-05-05 to 2013-05-22 and time series temporal range is from 1979-03-29 to 2017-03-15. Data were harmonised and quality controlled by ‘Hellenic Centre for Marine Research, Hellenic National Oceanographic Data Centre (HCMR/HNODC)’ from Greece. Regional datasets concerning contaminants are automatically harvested. Parameter names in these datasets are based on P01, BODC Parameter Usage Vocabulary, which is available at: https://vocab.seadatanet.org/p01-facet-search. Each measurement value has a quality flag indicator. The resulting data collections for each Sea Basin are harmonised, and the collections are quality controlled by EMODnet Chemistry Regional Leaders using ODV Software and following a common methodology for all Sea Regions. Harmonisation means that: (1) unit conversion is carried out to express contaminant concentrations with a limited set of measurement units (according to EU directives 2013/39/UE; Comm. Dec. EU 2017/848) and (2) merging of variables described by different “local names” ,but corresponding exactly to the same concepts in BODC P01 vocabulary. Detailed documentation is available at: https://doi.org/10.6092/8b52e8d7-dc92-4305-9337-7634a5cae3f4 Explore and extract data at: https://emodnet-chemistry.webodv.awi.de/contaminants%3EMediterranean The harmonised dataset can also be downloaded as ODV spreadsheet (TXT file), which is composed of metadata header followed by tab separated values. This worksheet can be imported to ODV Software for visualisation (More information can be found at: https://www.seadatanet.org/Software/ODV ). The same dataset is offered also as TXT file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms in subcomponents (measure, substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications users (e.g. LibreOffice Calc). The original datasets can be searched and downloaded from EMODnet Chemistry Chemistry CDI Data and Discovery Access Service: https://emodnet-chemistry.maris.nl/search

'''Short description:''' Multi-Year mono-mission satellite-based integral parameters derived from the directional wave spectra. Using linear propagation wave model, only wave observations that can be back-propagated to wave converging regions are considered. The dataset parameters includes partition significant wave height, partition peak period and partition peak or principal direction given along swell propagation path in space and time at a 3-hour timestep, from source to land. Validity flags are also included for each parameter and indicates the valid time steps along propagation (eg. no propagation for significant wave height close to the storm source or any integral parameter when reaching the land). The integral parameters at observation point are also available together with a quality flag based on the consistency between each propagated observation and the overall swell field.This product is processed by the WAVE-TAC multi-mission SAR data processing system. It processes data from the following SAR missions: Sentinel-1A and Sentinel-1B.One file is produced for each mission and is available in two formats: one gathering in one netcdf file all observations related to the same swell field, and for another all observations available in a 3-hour time range, and for both formats, propagated information from source to land. '''DOI (product) :''' https://doi.org/10.48670/moi-00174

This map presents all layers corresponding to "Other transportation support activities" activities in the Atlantic area. For more information about this NACE code : https://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=DSP_NOM_DTL_VIEW&StrNom=NACE_REV2&StrLanguageCode=EN&IntPcKey=18513344&IntKey=18513494&StrLayoutCode=HIERARCHIC&IntCurrentPage=1 Indicators collected are : Number of persons employed and number of employees in full time equivalent units per NUTS 3 unit of the Atlantic Area